Data Mining Algorithms in SSAS, Excel, and R

Don't use data mining as a black box. Get a deep understanding of how the data mining algorithms work. This knowledge is not only theoretical; it helps you developing better models in production.
Course info
Rating
(131)
Level
Intermediate
Updated
July 24, 2015
Duration
2h 59m
Table of contents
Introduction to Data Mining
Naive Bayes and Decision Trees
Linear Regression, Regression Trees, and Support Vector Machines
Linear Regression, Neural Network, and Models Evaluation
Time Series
Clustering
Association Rules and Sequence Clustering
Description
Course info
Rating
(131)
Level
Intermediate
Updated
July 24, 2015
Duration
2h 59m
Description

Data mining is gaining popularity as the most advanced data analysis technique. With modern data mining engines, products, and packages, like SQL Server Analysis Services (SSAS), Excel, and R, data mining has become a black box. It is possible to use data mining without knowing how it works. However, not knowing how the algorithms work might lead to many problems, including using the wrong algorithm for a task, misinterpretation of the results, and more. This course explains how the most popular data mining algorithms work, when to use which algorithm, and advantages and drawbacks of each algorithm as well. Demonstrations show the algorithms usage in SSAS, Excel, and R.

About the author
About the author

Dejan Sarka, MCT and SQL Server MVP, is an independent consultant, trainer, and developer focusing on database & business intelligence applications. His specialties are advanced topics like data modeling, data mining, and data quality.

More from the author
Working With Temporal Data in SQL Server
Intermediate
3h 6m
28 May 2014